 Synaptic Size Dynamics as an Effectively Stochastic ProcessAdiel Statman, Maya Kaufman, Amir Minerbi, Noam E Ziv and Naama Brenner PLOS Computational Biology, 2014, vol. 10, issue 10, 1-17 Abstract: Long-term, repeated measurements of individual synaptic properties have revealed that synapses can undergo significant directed and spontaneous changes over time scales of minutes to weeks. These changes are presumably driven by a large number of activity-dependent and independent molecular processes, yet how these processes integrate to determine the totality of synaptic size remains unknown. Here we propose, as an alternative to detailed, mechanistic descriptions, a statistical approach to synaptic size dynamics. The basic premise of this approach is that the integrated outcome of the myriad of processes that drive synaptic size dynamics are effectively described as a combination of multiplicative and additive processes, both of which are stochastic and taken from distributions parametrically affected by physiological signals. We show that this seemingly simple model, known in probability theory as the Kesten process, can generate rich dynamics which are qualitatively similar to the dynamics of individual glutamatergic synapses recorded in long-term time-lapse experiments in ex-vivo cortical networks. Moreover, we show that this stochastic model, which is insensitive to many of its underlying details, quantitatively captures the distributions of synaptic sizes measured in these experiments, the long-term stability of such distributions and their scaling in response to pharmacological manipulations. Finally, we show that the average kinetics of new postsynaptic density formation measured in such experiments is also faithfully captured by the same model. The model thus provides a useful framework for characterizing synapse size dynamics at steady state, during initial formation of such steady states, and during their convergence to new steady states following perturbations. These findings show the strength of a simple low dimensional statistical model to quantitatively describe synapse size dynamics as the integrated result of many underlying complex processes.Author Summary: Synapses are specialized sites of cell–cell contact that serve to transmit signals between neurons and their targets, most commonly other neurons. It is widely believed that changes in synaptic properties, driven by prior activity or by other physiological signals, represent a major cellular mechanism by which neuronal networks are modified. Recent experiments show that in addition to directed changes, synaptic sizes also change spontaneously, with dynamics that seem to have strong stochastic components. In spite of these dynamics, however, population distributions of synaptic sizes are remarkably stable, and scale smoothly in response to various perturbations. In this study we show that fundamental aspects of synapse size dynamics are captured remarkably well by a simple statistical model known as the Kesten process: the random-like nature of synaptic size changes; the stability and shape of synaptic size distributions; their scaling following various perturbations; and the kinetics of new synapse formation. These findings indicate that the multiple microscopic processes involved in determining synaptic size combine in such a way that their collective behavior buffers many of the underlying details. The simplicity of the model and its robustness provide a new route for understanding the emergence of invariants at the level of the synaptic population. Date: 2014 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1003846 DOI: 10.1371/journal.pcbi.1003846 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.